---
title: "Who cites Varun Chandrasekaran — 916 papers of our library"
description: "916 papers of the Elamur Research library cite the works of Varun Chandrasekaran, found in their bibliographies · page 1 of 2 · 1–100; the…"
canonical: "https://research.elamur.ai/free/en/authors/varun-chandrasekaran/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/varun-chandrasekaran/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Varun Chandrasekaran](https://md.research.elamur.ai/free/en/authors/varun-chandrasekaran/) / cited by

# Who cites Varun Chandrasekaran

916 citations of their works from 916 papers of our library (of the 149,439 whose bibliographies we read) · 192 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Varun Chandrasekaran](https://md.research.elamur.ai/free/en/authors/varun-chandrasekaran/)

**1** [2](https://md.research.elamur.ai/free/en/authors/varun-chandrasekaran/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/varun-chandrasekaran/cited-by/page/2/)

1. **[Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena](https://md.research.elamur.ai/free/en/papers/zheng-2023-judging-llm-judge-mt-bench/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.*2023 · 4,573 citations*
2. **[A Survey on Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,648 citations*
3. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations*
4. [**Direct Preference Optimization: Your Language Model is Secretly a Reward Model arXiv:2305.18290**Rafael Rafailov, Archit Sharma, Eric Mitchell, et al.*2023 · 2,896 citations*](https://md.research.elamur.ai/free/en/papers/rafailov-2023-direct-preference-optimization-language-model/)
5. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
6. [**Let's Verify Step by Step arXiv:2305.20050**Hunter Lightman, Vineet Kosaraju, Yura Burda, et al.*2023 · 1,412 citations*](https://md.research.elamur.ai/free/en/papers/lightman-2023-let-s-verify-step-step/)
7. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations*
8. **[MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI](https://md.research.elamur.ai/free/en/papers/yue-2023-mmmu-massive-multi-discipline-multimodal/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Xiang Yue, Yuansheng Ni, Kai Zhang, et al.*2023 · 1,005 citations*
9. **[Explainability for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhao-2023-explainability-large-language-models-survey/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Haiyan Zhao, Hanjie Chen, Fan Yang, et al.*2023 · 790 citations*
10. **[SGLang: Efficient Execution of Structured Language Model Programs](https://md.research.elamur.ai/free/en/papers/zheng-2023-sglang-efficient-execution-structured-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, et al.*2023 · 729 citations*
11. **[CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society](https://md.research.elamur.ai/free/en/papers/li-2023-camel-communicative-agents-mind/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, et al.*2023 · 706 citations*
12. [**ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs arXiv:2307.16789**Yujia Qin, Shihao Liang, Yining Ye, et al.*2023 · 589 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-toolllm-facilitating-large-language-models/)
13. [**A Categorical Archive of ChatGPT Failures arXiv:2302.03494**Ali Borji*2023 · 559 citations*](https://md.research.elamur.ai/free/en/papers/borji-2023-categorical-archive-chatgpt-failures/)
14. **[Gorilla: Large Language Model Connected with Massive APIs](https://md.research.elamur.ai/free/en/papers/patil-2023-gorilla-large-language-model-connected/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shishir G. Patil, Tianjun Zhang, Xin Wang, et al.*2023 · 546 citations*
15. [**Unleashing the potential of prompt engineering for large language models arXiv:2310.14735 · Patterns 6(6) 101,260 (2025)**Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.*2023 · 536 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-unleashing-potential-prompt-engineering-large/)
16. **[Sentiment Analysis in the Era of Large Language Models: A Reality Check](https://md.research.elamur.ai/free/en/papers/zhang-2023-sentiment-analysis-era-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenxuan Zhang, Yue Deng, Bing Liu, et al.*2023 · 506 citations*
17. [**MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts arXiv:2310.02255**Pan Lu, Hritik Bansal, Tony Xia, et al.*2023 · 468 citations*](https://md.research.elamur.ai/free/en/papers/lu-2023-mathvista-evaluating-mathematical-reasoning-foundation/)
18. **[OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems](https://md.research.elamur.ai/free/en/papers/he-2024-olympiadbench-challenging-benchmark-promoting-agi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chaoqun He, Renjie Luo, Yuzhuo Bai, et al.*2024 · 456 citations*
19. **[Mathematical Capabilities of ChatGPT](https://md.research.elamur.ai/free/en/papers/frieder-2023-mathematical-capabilities-chatgpt/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Simon Frieder, Luca Pinchetti, Alexis Chevalier, et al.*2023 · 449 citations*
20. **[The Internal State of an LLM Knows When It's Lying](https://md.research.elamur.ai/free/en/papers/azaria-2023-internal-state-llm-knows-when/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Amos Azaria, Tom Mitchell*2023 · 435 citations*
21. **[Automatic Prompt Optimization with “Gradient Descent” and Beam Search](https://md.research.elamur.ai/free/en/papers/pryzant-2023-automatic-prompt-optimization-gradient-descent/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Reid Pryzant, Dan Iter, Jerry Li, et al.*2023 · 409 citations*
22. [**ChatDev: Communicative Agents for Software Development arXiv:2307.07924**Chen Qian, Wei Liu, Hongzhang Liu, et al.*2023 · 385 citations*](https://md.research.elamur.ai/free/en/papers/qian-2023-chatdev-communicative-agents-software/)
23. **[Tool Learning with Foundation Models](https://md.research.elamur.ai/free/en/papers/qin-2023-tool-learning-foundation-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Yujia Qin, Shengding Hu, Yankai Lin, et al.*2023 · 383 citations*
24. [**WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct arXiv:2308.09583**Haipeng Luo, Qingfeng Sun, Can Xu, et al.*2023 · 372 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-wizardmath-empowering-mathematical-reasoning-large/)
25. [**MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities arXiv:2308.02490**Weihao Yu, Zhengyuan Yang, Linjie Li, et al.*2023 · 344 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-mm-vet-evaluating-large-multimodal/)
26. [**Textbooks Are All You Need II: phi-1.5 technical report arXiv:2309.05463**Yuanzhi Li, Sébastien Bubeck, Ronen Eldan, et al.*2023 · 336 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-textbooks-all-need-ii-phi/)
27. **[HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/guan-2023-hallusionbench-advanced-diagnostic-suite-entangled/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Tianrui Guan, Fuxiao Liu, Xiyang Wu, et al.*2023 · 335 citations*
28. **[Faith and Fate: Limits of Transformers on Compositionality](https://md.research.elamur.ai/free/en/papers/dziri-2023-faith-fate-limits-transformers-compositionality/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Nouha Dziri, Ximing Lu, Melanie Sclar, et al.*2023 · 327 citations*
29. **[Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/tong-2024-eyes-wide-shut-exploring-visual/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Shengbang Tong, Zhuang Liu, Yuexiang Zhai, et al.*2024 · 321 citations*
30. **[LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion](https://md.research.elamur.ai/free/en/papers/jiang-2023-llm-blender-ensembling-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dongfu Jiang, Xiang Ren, Bill Yuchen Lin*2023 · 321 citations*
31. [**MEDITRON-70B: Scaling Medical Pretraining for Large Language Models arXiv:2311.16079**Zeming Chen, Alejandro Hernandez Cano, Angelika Romanou, et al.*2023 · 315 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-meditron-70b-scaling-medical-pretraining/)
32. [**The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) arXiv:2309.17421**Zhengyuan Yang, Linjie Li, Kevin Lin, et al.*2023 · 311 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-dawn-lmms-preliminary-explorations-gpt/)
33. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
34. **[API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs](https://md.research.elamur.ai/free/en/papers/li-2023-api-bank-comprehensive-benchmark-tool/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Minghao Li, Yingxiu Zhao, Bowen Yu, et al.*2023 · 286 citations*
35. [**Ragas: Automated Evaluation of Retrieval Augmented Generation arXiv:2309.15217**Shahul Es, Jithin James, Luis Espinosa-Anke, et al.*2023 · 283 citations*](https://md.research.elamur.ai/free/en/papers/es-2023-ragas-automated-evaluation-retrieval-augmented/)
36. [**MiniCPM-V: A GPT-4V Level MLLM on Your Phone arXiv:2408.01800**Yuan Yao, Tianyu Yu, Ao Zhang, et al.*2024 · 269 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-minicpm-v-gpt-4v/)
37. **[DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models](https://md.research.elamur.ai/free/en/papers/wang-2023-decodingtrust-comprehensive-assessment-trustworthiness-gpt/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Boxin Wang, Weixin Chen, Hengzhi Pei, et al.*2023 · 259 citations*
38. **[Language Models can Solve Computer Tasks](https://md.research.elamur.ai/free/en/papers/kim-2023-language-models-solve-computer-tasks/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Geunwoo Kim, Pierre Baldi, Stephen McAleer*2023 · 249 citations*
39. **[MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2024-medagents-large-language-models-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiangru Tang, Anni Zou, Zhuosheng Zhang, et al.*2024 · 246 citations*
40. [**ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning arXiv:2304.06588**Petter Tornberg*2023 · 231 citations*](https://md.research.elamur.ai/free/en/papers/tornberg-2023-chatgpt-4-outperforms-experts-crowd/)
41. [**ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving arXiv:2309.17452**Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.*2023 · 225 citations*](https://md.research.elamur.ai/free/en/papers/gou-2023-tora-tool-integrated-reasoning-agent/)
42. [**Reinforced Self-Training (ReST) for Language Modeling arXiv:2308.08998**Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, et al.*2023 · 224 citations*](https://md.research.elamur.ai/free/en/papers/gulcehre-2023-reinforced-self-training-rest-language/)
43. [**Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment arXiv:2308.05374**Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li*2023 · 223 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-trustworthy-llms-survey-guideline-evaluating/)
44. [**AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors arXiv:2308.10848**Weize Chen, Yusheng Su, Jingwei Zuo, et al.*2023 · 217 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-agentverse-facilitating-multi-agent/)
45. [**TinyStories: How Small Can Language Models Be and Still Speak Coherent English?**Ronen Eldan, Yuanzhi Li*2023 · 213 citations*](https://md.research.elamur.ai/free/en/papers/eldan-2023-tinystories-small-language-models-still/)
46. **[Compressing Context to Enhance Inference Efficiency of Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-compressing-context-enhance-inference-efficiency/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yucheng Li, Bo Dong, Frank Guerin, et al.*2023 · 212 citations*
47. **[Sources of Hallucination by Large Language Models on Inference Tasks](https://md.research.elamur.ai/free/en/papers/mckenna-2023-sources-hallucination-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nick McKenna, Tianyi Li, Liang Cheng, et al.*2023 · 212 citations*
48. [**OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models arXiv:2308.13137**Wenqi Shao, Mengzhao Chen, Zhaoyang Zhang, et al.*2023 · 195 citations*](https://md.research.elamur.ai/free/en/papers/shao-2023-omniquant-omnidirectionally-calibrated-quantization-large/)
49. [**RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval arXiv:2401.18059**Parth Sarthi, Salman Abdullah, Aditi Tuli, et al.*2024 · 193 citations*](https://md.research.elamur.ai/free/en/papers/sarthi-2024-raptor-recursive-abstractive-processing-tree/)
50. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
51. **[Preference Ranking Optimization for Human Alignment](https://md.research.elamur.ai/free/en/papers/song-2023-preference-ranking-optimization-human-alignment/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Feifan Song, Bowen Yu, Minghao Li, et al.*2023 · 188 citations*
52. **[ToolQA: A Dataset for LLM Question Answering with External Tools](https://md.research.elamur.ai/free/en/papers/zhuang-2023-toolqa-dataset-llm-question-answering/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuchen Zhuang, Yue Yu, Kuan Wang, et al.*2023 · 182 citations*
53. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
54. [**GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts arXiv:2309.10253**Jiahao Yu, Xingwei Lin, Zheng Yu, et al.*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-gptfuzzer-red-teaming-large-language/)
55. [**GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher arXiv:2308.06463**Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-gpt-4-too-smart-safe/)
56. **[Long-form factuality in large language models](https://md.research.elamur.ai/free/en/papers/wei-2024-long-form-factuality-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jerry Wei, Chengrun Yang, Xinying Song, et al.*2024 · 165 citations*
57. [**FacTool: Factuality Detection in Generative AI — A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios arXiv:2307.13528**I-Chun Chern, Steffi Chern, Shiqi Chen, et al.*2023 · 160 citations*](https://md.research.elamur.ai/free/en/papers/chern-2023-factool-factuality-detection-generative-ai/)
58. **[TheoremQA: A Theorem-driven Question Answering Dataset](https://md.research.elamur.ai/free/en/papers/chen-2023-theoremqa-theorem-driven-question-answering/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenhu Chen, Ming Yin, Max Ku, et al.*2023 · 158 citations*
59. [**The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning arXiv:2312.01552**Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, et al.*2023 · 150 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-unlocking-spell-base-llms-rethinking/)
60. [**SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models arXiv:2307.10635**Xiaoxuan Wang, Ziniu Hu, Pan Lu, et al.*2023 · 149 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-scibench-evaluating-college-level-scientific/)
61. [**Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models arXiv:2312.06585**Avi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.*2023 · 147 citations*](https://md.research.elamur.ai/free/en/papers/singh-2023-human-data-scaling-self-training/)
62. **[ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings](https://md.research.elamur.ai/free/en/papers/hao-2023-toolkengpt-augmenting-frozen-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shibo Hao, Tianyang Liu, Zhen Wang, et al.*2023 · 147 citations*
63. [**Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration arXiv:2307.05300**Zhenhailong Wang, Shaoguang Mao, Wenshan Wu, et al.*2023 · 140 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-unleashing-emergent-cognitive-synergy-large/)
64. **[Theory of Mind for Multi-Agent Collaboration via Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-theory-mind-multi-agent-collaboration/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Huao Li, Yu Chong, Simon Stepputtis, et al.*2023 · 138 citations*
65. **[Deductive Verification of Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/ling-2023-deductive-verification-chain-thought-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhan Ling, Yunhao Fang, Xuanlin Li, et al.*2023 · 130 citations*
66. [**Time Travel in LLMs: Tracing Data Contamination in Large Language Models arXiv:2308.08493**Shahriar Golchin, Mihai Surdeanu*2023 · 128 citations*](https://md.research.elamur.ai/free/en/papers/golchin-2023-time-travel-llms-tracing-data/)
67. **[AceGPT, Localizing Large Language Models in Arabic](https://md.research.elamur.ai/free/en/papers/huang-2024-acegpt-localizing-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Huang Huang, Fei Yu, Jianqing Zhu, et al.*2024 · 127 citations*
68. [**Fine-tuning Language Models for Factuality arXiv:2311.08401**Katherine Tian, Eric Mitchell, Huaxiu Yao, et al.*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/tian-2023-fine-tuning-language-models-factuality/)
69. [**Generative Judge for Evaluating Alignment arXiv:2310.05470**Junlong Li, Shichao Sun, Weizhe Yuan, et al.*2023 · 125 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-generative-judge-evaluating-alignment/)
70. [**Large Language Model Alignment: A Survey arXiv:2309.15025**Tianhao Shen, Renren Jin, Yufei Huang, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-model-alignment-survey/)
71. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
72. [**Large Language Models Understand and Can be Enhanced by Emotional Stimuli arXiv:2307.11760**Cheng Li, Jindong Wang, Yixuan Zhang, et al.*2023 · 116 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-large-language-models-understand-enhanced/)
73. [**Fundamental Limitations of Alignment in Large Language Models arXiv:2304.11082**Yotam Wolf, Noam Wies, Oshri Avnery, et al.*2023 · 114 citations*](https://md.research.elamur.ai/free/en/papers/wolf-2023-fundamental-limitations-alignment-large-language/)
74. [**ALLaM: Large Language Models for Arabic and English arXiv:2407.15390**M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/bari-2024-allam-large-language-models-arabic/)
75. **[SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks](https://md.research.elamur.ai/free/en/papers/lin-2023-swiftsage-generative-agent-fast-slow/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Bill Yuchen Lin, Yicheng Fu, Karina Yang, et al.*2023 · 110 citations*
76. [**Evaluating the Performance of Large Language Models on GAOKAO Benchmark arXiv:2305.12474**Xiaotian Zhang, Chunyang Li, Yi Zong, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-evaluating-performance-large-language/)
77. **[GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers](https://md.research.elamur.ai/free/en/papers/li-2024-gsm-plus-comprehensive-benchmark-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qintong Li, Leyang Cui, Xueliang Zhao, et al.*2024 · 108 citations*
78. [**Exploring Large Language Models for Communication Games: An Empirical Study on Werewolf arXiv:2309.04658**Yuzhuang Xu, Shuo Wang, Peng Li, et al.*2023 · 97 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-exploring-large-language-models-communication/)
79. **[Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via Debate](https://md.research.elamur.ai/free/en/papers/xiong-2023-examining-inter-consistency-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Xiong, Xiao Ding, Yixin Cao, et al.*2023 · 94 citations*
80. **[Exploring the Potential of ChatGPT on Sentence Level Relations: A Focus on Temporal, Causal, and Discourse Relations](https://md.research.elamur.ai/free/en/papers/chan-2024-exploring-potential-chatgpt-sentence-level/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chunkit Chan, Cheng Jiayang, Weiqi Wang, et al.*2024 · 92 citations*
81. [**Universal Self-Consistency for Large Language Model Generation arXiv:2311.17311**Xinyun Chen, Renat Aksitov, Uri Alon, et al.*2023 · 92 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-universal-self-consistency-large-language/)
82. [**Language Modeling Is Compression arXiv:2309.10668**Gregoire Deletang, Anian Ruoss, Paul-Ambroise Duquenne, et al.*2023 · 91 citations*](https://md.research.elamur.ai/free/en/papers/deletang-2023-language-modeling-compression/)
83. [**Skywork: A More Open Bilingual Foundation Model arXiv:2310.19341**Tianwen Wei, Liang Zhao, Lichang Zhang, et al.*2023 · 91 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-skywork-more-open-bilingual/)
84. **[GAMA: A Large Audio-Language Model with Advanced Audio Understanding and Complex Reasoning Abilities](https://md.research.elamur.ai/free/en/papers/ghosh-2024-gama-large-audio-language-model/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sreyan Ghosh, Sonal Kumar, Ashish Seth, et al.*2024 · 87 citations*
85. **[Simulating Classroom Education with LLM-Empowered Agents](https://md.research.elamur.ai/free/en/papers/zhang-2025-simulating-classroom-education-llm-empowered/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Zheyuan Zhang, Daniel Zhang-Li, Jifan Yu, et al.*2025 · 84 citations*
86. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
87. **[EfficientQAT: Efficient Quantization-Aware Training for Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-efficientqat-efficient-quantization-aware-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengzhao Chen, Wenqi Shao, Peng Xu, et al.*2025 · 82 citations*
88. **[Multilingual Instruction Tuning With Just a Pinch of Multilinguality](https://md.research.elamur.ai/free/en/papers/shaham-2024-multilingual-instruction-tuning-just-pinch/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Uri Shaham, Jonathan Herzig, Roee Aharoni, et al.*2024 · 78 citations*
89. [**Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations arXiv:2303.18027**Jungo Kasai, Yuhei Kasai, Keisuke Sakaguchi, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/kasai-2023-evaluating-gpt-4-chatgpt-japanese/)
90. **[Systematic Biases in LLM Simulations of Debates](https://md.research.elamur.ai/free/en/papers/taubenfeld-2024-systematic-biases-llm-simulations-debates/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Amir Taubenfeld, Yaniv Dover, Roi Reichart, et al.*2024 · 76 citations*
91. **[Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training](https://md.research.elamur.ai/free/en/papers/fang-2024-enhancing-noise-robustness-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Feiteng Fang, Yuelin Bai, Shiwen Ni, et al.*2024 · 75 citations*
92. **[GPTEval: A Survey on Assessments of ChatGPT and GPT-4](https://md.research.elamur.ai/free/en/papers/mao-2024-gpteval-survey-assessments-chatgpt-gpt/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Rui Mao, Guanyi Chen, Xulang Zhang, et al.*2024 · 75 citations*
93. **[MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks](https://md.research.elamur.ai/free/en/papers/ahuja-2024-megaverse-benchmarking-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma, et al.*2024 · 74 citations*
94. **[Aligning Large and Small Language Models via Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/ranaldi-2024-aligning-large-small-language-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Leonardo Ranaldi, Andre Freitas*2024 · 70 citations*
95. **[Lion: Adversarial Distillation of Proprietary Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2023-lion-adversarial-distillation-proprietary-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuxin Jiang, Chunkit Chan, Mingyang Chen, et al.*2023 · 70 citations*
96. **[AraDiCE: Benchmarks for Dialectal and Cultural Capabilities in LLMs](https://md.research.elamur.ai/free/en/papers/mousi-2025-aradice-benchmarks-dialectal-cultural-capabilities/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Basel Mousi, Nadir Durrani, Fatema Ahmad, et al.*2025 · 68 citations*
97. [**CMATH: Can Your Language Model Pass Chinese Elementary School Math Test? arXiv:2306.16636**Tianwen Wei, Jian Luan, Wei Liu, et al.*2023 · 67 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-cmath-language-model-pass/)
98. **[A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners](https://md.research.elamur.ai/free/en/papers/jiang-2024-peek-into-token-bias-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bowen Jiang, Yangxinyu Xie, Zhuoqun Hao, et al.*2024 · 64 citations*
99. **[ToMBench: Benchmarking Theory of Mind in Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2024-tombench-benchmarking-theory-mind-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhuang Chen, Jincenzi Wu, Jinfeng Zhou, et al.*2024 · 62 citations*
100. [**Large Language Models Are Not Strong Abstract Reasoners arXiv:2305.19555**Gael Gendron, Qiming Bao, Michael Witbrock, et al.*2023 · 61 citations*](https://md.research.elamur.ai/free/en/papers/gendron-2023-large-language-models-strong-abstract/)

**1** [2](https://md.research.elamur.ai/free/en/authors/varun-chandrasekaran/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/varun-chandrasekaran/cited-by/page/2/)

- [← back to](https://md.research.elamur.ai/free/en/authors/varun-chandrasekaran/) — Varun Chandrasekaran